Accurate calculation of spin-state energy gaps in Fe(iii) spin-crossover systems using density functional methods

Abstract

A survey of different Density Functional methods shows that the B3LYP* functional is the most accurate one in terms of predicting spin-state energy gaps on Fe(iii) complexes and whether they will or not exhibit spin-crossover behavior.

Push and Pull Effect of Methoxy and Nitro Groups Modifies the Spin-State Switching Temperature in Fe(III) Complexes

“…B0.1) 24 electronic structure package with a 10 –8 convergence criterion for the density matrix elements using the latest triple-ζ basis set with polarization functions for all elements (def2-TZVP). 25 The exchange-correlation functional B3LYP*, 26 which was recently reported to be the most accurate one toward Fe(III) system in terms of spin-state energy gaps, 27 was used for all system. The corresponding vibrational analysis was done for all optimized structures to ensure that they were minima along the potential energy surface.…”

Fine-tuning of the spin-crossover properties of Fe(iii) complexes via ligand design

“…38,[93][94][95] Recently, we have benchmarked several DFT methods against a large data set of Fe(III) SCO systems. 96 From that study, it was clear that both TPSSh 97,98 and B3LYP* 99 are able to correctly predict the energy window for SCO to occur in such systems and, in particular, B3LYP* was able to minimize the error with respect to the calculation of the corresponding T 1/2 . B3LYP* has been also benchmarked against correlated multiconfigurational wave function calculations and proven to provide accurate geometries, vibrational frequencies, spin-state energy gaps and absorption spectra for Fe(III) SCO systems.…”

Exploring the computational design of anionic spin-crossover systems

“…Because of this intrinsic problem, the use of computational tools has helped in gaining insight into how to modulate the transition temperature in SCO systems, using a broad range of electronic structural methods at different levels of theory as well as machine learning protocols. [37][38][39][40][41][42][43][44] Most SCO systems are either neutral or positively charged, but very few of them have been reported having a total negative charge. [45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62] The lack of more anionic SCO systems is somehow problematic because such systems are key components in the design of fluorescent multifunctional materials and conducting switchable materials.…”

“…Because of this intrinsic problem, the use of computational tools has helped in gaining insight into how to modulate the transition temperature in SCO systems, using a broad range of electronic structural methods at different levels of theory as well as machine learning protocols. 37–44…”